A simple strategy for changing a brittle conducting polymer (PEDOT:PSS) into a solution‐processed highly deformable viscoelastic polymer is presented. Rapid self‐healing of conductivity, ...customer‐designed LEDs with complex micropatterns, and foldable stretchable LEDs are demonstrated.
The generalized fractional Maxwell model, formulated for hyperelastic material within the framework of the nonlinear viscoelasticity with internal variables, is applied to identify viscoelastic ...constitutive equations from layer-specific experimental data obtained by uniaxial harmonic loading of ex-vivo human descending thoracic aortas. The constitutive parameters are identified by using a genetic algorithm for the optimal fitting of the experimental data. The accuracy of the fitted fractional model is compared to the fitted integer order model with the same number of Maxwell elements. The formulation of an original strain energy density function for anisotropic nonlinear viscoelasticity is introduced and constitutive parameters are obtained from the experiments.
Magneto‐Responsive Bistable Structures
The combination of viscoelasticity and magneto‐mechanics fundamentals conceptualizes a new designing concept for bistable structures. In article number 2313865, ...Daniel Garcia‐Gonzalez and co‐workers conceive a computational and experimental platform to translate these fundamentals into functional applications. The transient and steady bistable transitions of these structures can be modulated by the application rate of external magnetic stimuli, removing the need for continuous actuation.
In this study we present a nonlinear complicance/elastance model which also considers the viscoelasticity of the lung tissue in combination with air compressibility to achieve a high accuracy ...calculation of muscle pressure waveform. ...on the contrary to the common perception, increase in the inhale flow causes a reduction in the instantaneous plural pressure, so the model have to be revised as following:
Recent fracture experiments using the Rivlin–Thomas pure-shear geometry in rubbery viscoelastic materials have suggested nucleation of cracks at a critical stretch, independent on loading rate. For ...linear material using the rate-independent cohesive model theory, the critical elongation between grips (in a quite general testing geometry) at nucleation is instead monotonically decreasing with rate of up to the square root of the ratio between the instantaneous and relaxed elastic modulus of the material. Shrimali & Lopez-Pamies have made the assumption of a constant critical stretch to develop a theory which contrasts therefore with classical models. However, we further generalize the Rivlin–Thomas theory by assuming an arbitrary relation between nucleation stretch and loading rate, which therefore includes both models as limit cases. We present a simple case of a Double Cantilever Beam (DCB) geometry with linear standard materials, to show an analytical example.
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The rheology of ultrasoft materials like the human brain is highly sensitive to regional and temporal variations and to the type of loading. While recent experiments have shaped our ...understanding of the time-independent, hyperelastic response of human brain tissue, its time-dependent behavior under various loading conditions remains insufficiently understood. Here we combine cyclic and relaxation testing under multiple loading conditions, shear, compression, and tension, to understand the rheology of four different regions of the human brain, the cortex, the basal ganglia, the corona radiata, and the corpus callosum. We establish a family of finite viscoelastic Ogden-type models and calibrate their parameters simultaneously for all loading conditions. We show that the model with only one viscoelastic mode and a constant viscosity captures the essential features of brain tissue: nonlinearity, pre-conditioning, hysteresis, and tension-compression asymmetry. With stiffnesses and time constants of μ∞=0.7kPa, μ1=2.0kPa, and τ1=9.7s in the gray matter cortex and μ∞=0.3kPa, μ1=0.9kPa and τ1=14.9s in the white matter corona radiata combined with negative parameters α∞ and α1, this five-parameter model naturally accounts for pre-conditioning and tissue softening. Increasing the number of viscoelastic modes improves the agreement between model and experiment, especially across the entire relaxation regime. Strikingly, two cycles of pre-conditioning decrease the gray matter stiffness by up to a factor three, while the white matter stiffness remains almost identical. These new insights allow us to better understand the rheology of different brain regions under mixed loading conditions. Our family of finite viscoelastic Ogden-type models for human brain tissue is simple to integrate into standard nonlinear finite element packages. Our simultaneous parameter identification of multiple loading modes can inform computational simulations under physiological conditions, especially at low to moderate strain rates. Understanding the rheology of the human brain will allow us to more accurately model the behavior of the brain during development and disease and predict outcomes of neurosurgical procedures.
While recent experiments have shaped our understanding of the time-independent, hyperelastic response of human brain tissue, its time-dependent behavior at finite strains and under various loading conditions remains insufficiently understood. In this manuscript, we characterize the rheology of human brain tissue through a family of finite viscoelastic Ogdentype models and identify their parameters for multiple loading modes in four different regions of the brain. We show that even the simplest model of this family, with only one viscoelastic mode and five material parameters, naturally captures the essential features of brain tissue: its characteristic nonlinearity, pre-conditioning, hysteresis, and tension-compression asymmetry. For the first time, we simultaneously identify a single parameter set for shear, compression, tension, shear relaxation, and compression relaxation loading. This parameter set is significant for computational simulations under physiological conditions, where loading is naturally of mixed mode nature. Understanding the rheology of the human brain will help us predict neurosurgical procedures, inform brain injury criteria, and improve the design of protective devices.
Macromolecular phase separation is being recognized for its potential importance and relevance as a driver of spatial organization within cells. Here, we describe a framework based on synergies ...between networking (percolation or gelation) and density (phase separation) transitions. Accordingly, the phase transitions in question are referred to as phase separation coupled to percolation (PSCP). The condensates that result from PSCP are viscoelastic network fluids. Such systems have sequence-, composition-, and topology-specific internal network structures that give rise to time-dependent interplays between viscous and elastic properties. Unlike pure phase separation, the process of PSCP gives rise to sequence-, chemistry-, and structure-specific distributions of clusters that can form at concentrations that lie well below the threshold concentration for phase separation. PSCP, influenced by specific versus solubility-determining interactions, also provides a bridge between different observations and helps answer questions and address challenges that have arisen regarding the role of macromolecular phase separation in biology.
Mittag and Pappu summarize a framework for biomolecular condensate formation that is based on phase separation coupled with percolation. This framework helps address recent challenges and helps highlight the fact that condensates are viscoelastic materials possessing distinctive internal structures and material properties that are sequence-, architecture-, and composition-specific.
